This invention relates to mobile wireless communication systems.
In a typical wireless communication system, each device, e.g., a user equipment (UE), a base station (BS), etc., has a local oscillator (LO) that defines a local time reference. It is important for the LOs of devices communicating with each other to be aligned as precisely as possible. If two devices' LOs are not aligned, their time references drift in relation to each other, which can result in the devices' being no longer capable of receiving information properly from each other and in loss of the connection.
LO alignment is particularly important to wireless communication systems like wideband code division multiple access (WCDMA) mobile telephone systems and other digital mobile telephone systems. In such systems, a typical receiver uses automatic frequency control (AFC) to adjust its LO so that it aligns well with the LO(s) of the transmitter(s) to which it is connected.
A WCDMA communication system uses direct-sequence spread-spectrum techniques. Pseudo-noise scrambling codes and orthogonal channelization codes separate BSs and physical communication channels, respectively, in the downlink (BS-to-UE) and uplink (UE-to-BS) directions. Scrambling and channelization codes are well known in the art, and WCDMA and other third-generation (3G) and future communication systems operate in accordance with standards promulgated by the Third Generation Partnership Project (3GPP).
High-speed downlink (DL) packet access (HSDPA) is an evolution of WCDMA communication systems that provides higher bit rates by using higher order modulation, multiple spreading codes, adaptive forward error correction (FEC), and DL-channel feedback information. The DL-channel feedback information is information sent by a UE to a BS through the uplink (UL) channel regarding the DL channel's quality. The cell providing HSDPA service is usually called the “serving” cell, and the serving cell uses the DL-channel feedback information to optimize the DL modulation and coding for throughput.
Of course, AFC operation is almost never perfect, which is to say that there is almost always a non-zero frequency difference between the LOs of the transmitting and receiving devices even with AFC. The operation of a typical AFC involves studying communication-channel parameters over time and attempting to adjust an LO based on at least those parameters. For example, complex-valued estimates of the impulse response of the communication channel might be studied over time, and the adjustment of the LO may be done such that no rotation of the channel estimates is seen in the complex (or I-Q) plane. That kind of adjustment is based on the fact that rotation in the I-Q plane corresponds to relative frequency drift of the LOs, which in turn corresponds to relative time reference drift.
FIG. 1 is a block diagram of an apparatus 100, which may be a portion of a receiver in a typical UE or BS, and depicts the operation of a typical AFC. A voltage-controlled crystal oscillator (VCXO) 102 generates the LO signal used by a receiver front end (RX Fe) 104. The frequency of the LO signal produced by the VCXO 102 is responsive to a control signal ferr generated by an AFC 106, and as illustrated, the control signal produced by the AFC 106 may be converted to an analog control voltage by a digital-to-analog converter (DAC) 107. The LO frequency set by the AFC 106 is called the “AFC frequency” in this application. In the arrangement depicted in FIG. 1, the AFC 106 generates the control signal ferr based on channel estimates ĥf produced by a channel estimator 108, which typically provides such estimates to other devices in the receiver, including for example a RAKE combiner 110 and a signal-to-interference ratio (SIR) estimator 112. The channel estimator 108 generates the channel estimates from correlated signals provided by a de-spreader 114, which generates the correlated signals from signals from the RX Fe 104. Correlated signals from the de-spreader 114 are selectively combined based on the channel estimates by the RAKE combiner 110.
De-spreading, channel estimation, and RAKE combining are well known in the art. Channel estimation generally involves multiplying the correlated signals with the complex conjugates of known signals (or pilots), and possibly averaging the results over time. U.S. Patent Application Publication No. 2005/0105647 by Wilhelmsson et al. for “Channel Estimation by Adaptive Interpolation” describes channel estimation in a communication system using orthogonal frequency division multiplex. RAKE combining is described in, for example, John G. Proakis, “Digital Communications”, 3rd ed., pp. 797-806, McGraw-Hill; and U.S. Pat. No. 6,922,434 by Wang et al. for “Apparatus and Methods for Finger Delay Selection in Rake Receivers”. Signals from the RAKE combiner 110 and SIR estimator 112 are typically used in further processing operations carried out by the UE or other receiver.
A typical AFC 106 periodically reports a single frequency error ferr that is a weighted combination of frequency errors of respective de-spread fingers, although it will be understood that this is just one of many possible examples. One or more channel estimates ĥf are collected for each finger f during a given time period, e.g., during each of the successive time slots into which the received signal is organized. The current channel estimate(s) ĥf and channel estimates collected in the previous period ĥfprevious determine a value y, which is given by:
  y  =            ∑      f        ⁢                                                      h              ^                        f                    ⁡                      (                                          h                ^                            f              previous                        )                          *            .      where the asterisk denotes complex conjugation. The value y may be filtered, for example according to:yfilt=λ(y−yfiltprevious)+yfiltprevious where yfilt is the current filtered value, λ is a filter parameter, and yfiltprevious is the filtered value for the previous period or previous channel estimate. It will be understood that the filter state is appropriately initialized or reset from time to time. The frequency error ferr is then given by:ferr=φ/2πΔt where the phase angle φ=arg(yfilt) and Δt is the time interval between two consecutive updates of the AFC (e.g., two consecutive collected channel estimates). For just two of many possible examples, Δt may be 1/1500s or 1/7500s. These computations are conveniently called “typical AFC computations” in this application.
Besides the weighted combination that results from the summation over de-spread fingers, other combinations of the fingers' frequency errors are possible. For example, an unweighted combination or the median value can be used. U.S. patent application Ser. No. 09/678,907 by Dent et al., which corresponds to International Patent Publication No. WO 02/29978 A2 and which is now U.S. Pat. No. 7,443,826, describes use of simply the frequency error of the strongest de-spread finger. When applicable, the reported frequency error may also be equal to that of an HSDPA serving cell. The differences between the AFC frequency and the frequencies of the respective de-spread fingers are called “residual frequency offsets” in this application.
In low-relative-velocity situations, the frequency differences between the fingers, and thus the residual frequency offsets, due to Doppler shifts are usually not large, but in high-relative-velocity situations, the frequency differences and residual frequency offsets can be large enough to degrade receiver performance. For example, channel estimation, power estimation, interference estimation, SIR estimation, relative channel gain estimation (e.g., the difference between the common pilot channel (CPICH) and dedicated physical channel (DPCH) in a WCDMA communication system), and combining can be affected by large residual frequency offsets.
U.S. patent application Ser. No. 09/678,907 describes compensating for residual frequency offsets in a receiver chain. The compensation can include estimation of a residual frequency offset for each finger ferr,fres, and frequency error correction (de-rotation) of received, de-spread symbols for each finger f or for each cell (transmitter). Such compensation can enhance receiver performance in high-velocity situations or when the LOs are not well aligned in frequency, but for a receiver to apply the compensation, a channel estimator having increased complexity is needed. The compensation itself can also introduce additional operations that must be carried out. The additional complexity of this compensation strategy is costly and thus can be undesirable.
As depicted in FIG. 1, a receiver can include a Doppler-spread estimator 116 that is sometimes also used as a velocity estimator. A typical Doppler estimator applies either an argument- (or zero-) crossing algorithm or a level-crossing algorithm, for example, to received signals. A variant of the argument-crossing algorithm counts the number of times that the complex channel estimate crosses either of the I and Q axes. The level-crossing algorithm counts the number of times the absolute value of the complex channel estimate crosses a given level. Estimates of the Doppler spread can be used to set operation mode and parameter values for various blocks in the receiver chain, e.g., the AFC 106, the RAKE combiner 110 (which may alternatively be a generalized RAKE or other type of RAKE receiver or signal equalizer), the SIR estimator 112, as well as an estimator of the relative channel gain (part of the further processing indicated generally in FIG. 1).
A conventional Doppler estimator is a poor velocity estimator because the conventional Doppler estimator bases its estimates on the Rayleigh fading properties of the strongest signal paths, or de-spread fingers. Thus, the conventional Doppler estimator is inappropriate for situations having weak or no fading, e.g., line-of-sight (LOS) communication conditions where the strongest path is typically dominant and has a Ricean distribution. In the context of a UE in a 3G mobile telephone system, those situations include passing close by a BS. It is thus desirable to be able to generate velocity estimates that avoid the problems of conventional Doppler estimators.